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Research on Optimization of Cutting Parameters for Guided Wave Plate

Author: WangJun
Tutor: ZhangShuRen
School: Changchun University of Science and Technology
Course: Mechanical Manufacturing and Automation
Keywords: genetic algorithm BP neural network surface roughness multi-objective optimization cutting parameter
CLC: TJ05
Type: Master's thesis
Year: 2011
Downloads: 29
Quote: 0
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Abstract


According to the high-quality requests of the production and processing of thin-walled parts of weapons and equipment, we did the job of the arrangement of process route, basic fixture design, stress deformation analysis and CNC machining simulation in this article. We studied the optimization of the technological parameter (mainly the three cutting elements) by using nonlinear regression method, genetic algorithm and the BP neural network, to seek the optimal solution which can guide actual production and achieve the purpose of reduce the surface roughness of requirements and the production cost.In this paper, we established the forecasting model of the surface roughness by using the nonlinear regression method, and then established multi-objective optimization function which combined production cost and the surface roughness. In view of processing requirements and the performance of machine and tools, we limited the selection range of the three cutting elements. Next step we used the GA part of the MATLAB software to carry on the optimization which maked us achieve the optimal solution by using expert method., and applied the results to the practical production processing. After all, we compared the result of the surface roughness predicted by using BP neural network with the result obtained by actual production.

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CLC: > Industrial Technology > Arms industry > General issues > Manufacturing processes and equipment
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